SECTORS · DOMAIN SYSTEMS
Domain knowledgechanges the product.
The same technology produces very different systems in different sectors. Where that difference sits — in regulation, in data, in how the work actually gets done — is usually the whole engagement.
SECTORS
Where we have built before.
APPROACH
Sector knowledge is an engineering input.
Domain expertise is often described as a sales credential. In practice it is an engineering one: it determines the data model, the failure modes that matter, the audit requirements, and which parts of a workflow can be automated at all.
A claims system and an order management system look similar on a whiteboard. They diverge completely once you account for who is accountable for a decision, how long records must be kept, and what has to happen when a step fails halfway.
01
Discover
Understand the business, the users, the constraints and the actual opportunity — including where software is not the answer.
02
Architect
Define the product, the AI approach, the data model and the system architecture, with the trade-offs written down rather than assumed.
03
Build
Engineer the software and the intelligence layers together, in short cycles, against criteria agreed before work started.
04
Validate
Test functionality, quality, security and — where models are involved — behaviour, against inputs that reflect real use.
05
Deploy
Launch through infrastructure and pipelines built for repeatable release, with a rollback path that has been exercised.
06
Evolve
Observe how the system behaves in production, improve it against that evidence, and scale what is working.
NEXT STEP
Which sector are you building in?
Tell us the domain and the constraint you are up against. That combination usually determines the architecture before anything else does.